Gaps in the evidence base - the potentials of big data

Planning for functional, cross-border corridors has been challenging due to the various territorial boundaries. Understanding both micro- and macro-level dynamics and mobilities has become increasingly important in transnational corridor development that in the end aims at affecting the behavioral patterns of individual citizens and companies, often crossing national boundaries.

But corridors, as settings for comprehensive governance, require a wide understanding of relationships between different policy sectors and scales as well as how the various datasets and indicators can be better used to measure these relationships. And we still need to develop a broader understanding of flows and interactions, to support this comprehensive governance that relies on versatile utilisation of data.

There are three dimensions that integrated territorial policymaking and data-driven corridor governance should take into account:

  • the physical dimension that describes the corridor as an axis for transportation flows and urbanisation
  • the social dimension that describes the corridor as a framework for social interaction, and
  • the digital dimension that describes the corridor as a platform for digital flows and interactions

The combination of data representing these dimensions provides a richer picture of what happens in growth corridors. And although the factors behind movements within growth corridors should be at the very core of corridor development, such insights would include more than the physical movement of vehicles, material, or people through space and time. They would also describe social and digital interactions and flows.

There are currently very few detailed analyses about the functionality of growth corridors, highlighting the potential of big data in increasing the understanding of connectivities along such corridors. Various knowledge gaps and challenges have been identified concerning the development of functional corridors, dealing for example with:

  • conventional approaches: Most of the datasets used in corridor development today still represent rather conventional ways of approaching territorial development from the perspective of established units and scales of territorial administration
  • weak utilisation of spatial data: The overall utilisation of spatial data that adequately captures the functionalities of corridors related, for example, to daily mobilities and interactive practices has been so far rather weak in planning processes. This is partly because of the lack of appropriate competencies in data utilisation
  • absence of big data or absence of spatial dimension from big data: Very often the absence of location-based or temporal data is the main limiting factor preventing high-resolution depictions of flows and interactions
  • sharing of data: Private companies often own some of the most promising datasets describing corridor functionalities, thus creating a challenge for data accessibility
  • ethical concerns: Ethical issues and privacy concerns, as well as a lack of ground truth data, hinders the utilisation of new datasets

It is possible to have a more comprehensive understanding of flows and interactions by utilising new data sources, and especially big data. In order to generate insights from large datasets for corridor development we need to take into account some of the following issues:

  • increased understanding of functionality: As corridor-based development is still largely based on data that is tied to the traditional units of territorial administration, the use of new data sources can make corridors more understandable and thus a legitimate basis for territorial policymaking. Increased understanding can also act as a basis for targeting policy measures
  • service provision in functional corridors: Utilisation of new data sources can act as a trigger for new services, and vice versa, services can trigger new kind of corridor functionality. For example, sustainability-driven solutions related to smooth mobility and travel chains often rely on the utilisation of big and real-time data
  • cross-border functionality: Cross-border movements can be assessed more accurately, for example, based on the roaming or sensor data. Big data has the potential to renew or even disrupt cross-border corridor governance based on new collaborative business models between public and private actors

You can read more about the Potentials of big data for integrated territorial policy development in the European growth corridors